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dc.contributor.authorBehnia, Arash
dc.contributor.authorRanjbar, Navid
dc.contributor.authorChai, Hwa Kian
dc.contributor.authorMasaeli, Mahyar
dc.date.accessioned2019-04-01T00:45:39Z
dc.date.available2019-04-01T00:45:39Z
dc.date.issued2016
dc.identifier.issn0950-0618
dc.identifier.doi10.1016/j.conbuildmat.2016.06.130
dc.identifier.urihttp://hdl.handle.net/10072/100486
dc.description.abstractThis paper introduces suitable features and methods to define hazard rate function by acoustic emission (AE) parametric analysis to develop robust damage statement index and reliability analysis. AE signal energy was first examined to find out the relation between damage progress and AE signal energy so that a damage index based on AE signal energy could be proposed to quantify progressive damage imposed to ferrocement composite slabs. Moreover, by using AE signal strength, historic index could be computed and utilized to develop a modified hazard rate function through integration of bathtub curve and Weibull function. Furthermore, to provide a practical scheme for real condition monitoring, support vector regression was utilized to produce a robust tools for failure prediction considering uncertainties exist in real structures.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofpagefrom823
dc.relation.ispartofpageto832
dc.relation.ispartofjournalConstruction and Building Materials
dc.relation.ispartofvolume122
dc.subject.fieldofresearchCivil engineering
dc.subject.fieldofresearchCivil engineering not elsewhere classified
dc.subject.fieldofresearchBuilding
dc.subject.fieldofresearchcode4005
dc.subject.fieldofresearchcode400599
dc.subject.fieldofresearchcode3302
dc.titleFailure prediction and reliability analysis of ferrocement composite structures by incorporating machine learning into acoustic emission monitoring technique
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.hasfulltextNo Full Text
gro.griffith.authorMasaeli, Mahyar


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